RFVis provides a command line tool as well as a GUI to render botanically inspired 2D representations of a Random Forest.
SyB3R allows to generate realistic images (including motion blur, noise, depth of field, etc.) along with ground truth for scene depth to benchmark SfM and MVS methods.
MVMS3D is a multi-view stereo tool that uses multiple shots per view point to increase the SNR and obtain a more complete 3D reconstruction. (The corresponding paper won the Best Paper by Young Authors Award at the ISPRS Congress 2016.)
StructuredRF aims to exploit densely labelled images for structured prediction.
SpeculaR implements an approach to detect and remove specular, shadow, or occluded regions in images of planar objects by replacing them with meaningful information from additional views.
GPU-BA provides GPU implementations of three different methods for bundle adjustment, namely the commonly used second order method based on Levenberg-Marquardt in two variations, as well as the two first order methods nonlinear conjugate gradients and alternating resection-intersection.
DropTrack implements a pipeline to detect and tracks drops in high-speed image sequences of a test cell developed at the Chair of Chemical and Process Engineering of Technische Universität Berlin.
UIPF is an open-source framework that allows to develop, implement, and visualize image processing tool chains.
VisualRF provides a Matlab script to render a given Random Forest Classifier as a set of visual binary trees in 3D.
FPCF implements an automatic, robust, and efficient fusion framework for point clouds ( in particular MS Kinect data ) based on coarse feature based alignment and fine ICP alignment.